Geological effects can impact the design and successful completion of oil, gas, and geothermal wells. Understanding the stresses and pore pressures within the subsurface are important to development of a geomechanical model that can guide well design as part of an integrated process to minimize cost and maximize safety. The normals to the three orthogonal planes define a Cartesian coordinate system (x1, x2, and x3). The stress tensor has nine components, each of which has an orientation and a magnitude (see Figure 1.a). Three of these components are normal stresses, in which the force is applied perpendicular to the plane (e.g., S11 is the stress component acting normal to a plane perpendicular to the x1-axis); the other six are shear stresses, in which the force is applied along the plane in a particular direction (e.g., S12 is the force acting in the x2-direction along a plane perpendicular to the x1-axis).
The objective of the project is to reconcile and quantify the impact of geological and completion variables that cause significant EUR differences in two recent wells drilled and completed in the Uteland Butte member of the Green River formation in Uinta Basin, Utah. While the geology and reservoir conditions are similar for both wells, the completion design and parameters are different (Ball-and-Sleeve vs. Plug-and-Perf, job size, treatment rates, well length, etc.).
The Asset Team uses a structured workflow consisting of several modeling tools: Rate-Transient-Analysis (RTA), Frac Modeling (FM) and Reservoir Simulation (RS) to address and quantify the impact of each variable: Job size, Treatment Rate, Frac count per Stage, Well Length and the effect of clays.
The workflow began with a performance evaluation of the high EUR well (Plug-and-Perf, large job) with RTA and Frac modeling; followed by history-match and prediction of the EUR with the RS model. In the subsequent workflow, a single variable is changed in each modeling step, while others are held constant -- as such, the EUR impact for each variable can be quantified. The result from each step is calibrated with the actual performance observed in the field.
This model-based approach successfully quantified the production impact of each variable. Subsequently, the key drivers can be determined which explains the estimated EUR difference between the two wells. This work drives us to conclude that due to varying pressure, PVT and lithology across the field, different completion designs shall be utilized. The team has gained valuable insight on how to implement different completion techniques with varying job size and design for the basin. Currently, these results are used to drive the well designs and approval; with the long-term objective of optimizing the Field Development Plan.
You, Junyu (Petoleum Recovery Research Center) | Ampomah, William (Petoleum Recovery Research Center) | Kutsienyo, Eusebius Junior (Petoleum Recovery Research Center) | Sun, Qian (Petoleum Recovery Research Center) | Balch, Robert Scott (Petoleum Recovery Research Center) | Aggrey, Wilberforce Nkrumah (KNUST) | Cather, Martha (Petoleum Recovery Research Center)
This paper presents an optimization methodology on field-scale numerical compositional simulations of CO2 storage and production performance in the Pennsylvanian Upper Morrow sandstone reservoir in the Farnsworth Unit (FWU), Ochiltree County, Texas. This work develops an improved framework that combines hybridized machine learning algorithms for reduced order modeling and optimization techniques to co-optimize field performance and CO2 storage.
The model's framework incorporates geological, geophysical, and engineering data. We calibrated the model with the performance history of an active CO2 flood data to attain a successful history matched model. Uncertain parameters such as reservoir rock properties and relative permeability exponents were adjusted to incorporate potential changes in wettability in our history matched model.
To optimize the objective function which incorporates parameters such as oil recovery factor, CO2 storage and net present value, a proxy model was generated with hybridized multi-layer and radial basis function (RBF) Neural Network methods. To obtain a reliable and robust proxy, the proxy underwent a series of training and calibration runs, an iterative process, until the proxy model reached the specified validation criteria. Once an accepted proxy was realized, hybrid evolutionary and machine learning optimization algorithms were utilized to attain an optimum solution for pre-defined objective function. The uncertain variables and/or control variables used for the optimization study included, gas oil ratio, water alternating gas (WAG) cycle, production rates, bottom hole pressure of producers and injectors. CO2 purchased volume, and recycled gas volume in addition to placement of new infill wells were also considered in the modelling process.
The results from the sensitivity analysis reflect impacts of the control variables on the optimum results. The predictive study suggests that it is possible to develop a robust machine learning optimization algorithm that is reliable for optimizing a developmental strategy to maximize both oil production and storage of CO2 in aqueous-gaseous-mineral phases within the FWU.
This paper provides perspective on the current state of multizone completion technology and issues encountered in the industry with developing a system that offers increased capabilities to meet the increasing challenges presented by the Lower Tertiary in the Gulf of Mexico. The lower tertiary formation found in the pre-salt layers of the Gulf of Mexico has become a proving ground for extending what is possible when completing multistage fracturing in ultradeepwater wells.
This paper covers the staged field-development methodology, including analysis and evaluation of various development concepts, that enabled the company to optimize both completion design and artificial-lift selection, reducing downtime and lowering operating costs by nearly 50%. Completion engineers feel pressure to maximize production per acre and minimize the downsides of fracturing in tight spaces. Terry Palisch, talks about promoting knowledge sharing as part of JPT’s tech director report. Seismic stimulation, achievable with the implementation of a single tool, requires significantly lower investments than gas, thermal, and chemical injection methods, with minimal environmental impact. This paper describes an experimental study with a new propellant and aims to understand the pattern of fracture creation with these propellants.
The basic objective of this course is to introduce the overview and concept of production optimisation, using nodal analysis as a tool in production optimisation and enhancement. The participants are exposed to the analysis of various elements that help in production system starting from reservoir to surface processing facilities and their effect on the performance of the total production system. Depth conversion of time interpretations is a basic skill set for interpreters. There is no single methodology that is optimal for all cases. Next, appropriate depth methods will be presented. Depth imaging should be considered an integral component of interpretation. If the results derived from depth imaging are intended to mitigate risk, the interpreter must actively guide the process.
The explorer has so far encountered 400 ft of reservoir pay zone in an area where it has three other producing fields. Murphy Oil to Buy Deepwater US Gulf Assets for up to $1.625 Billion The El Dorado, Arkansas-based Murphy has quickly found a home for some of the cash it will receive from the sale of its Malaysia business. The company has been rapidly expanding its US gulf footprint while simplifying its portfolio and targeting more oil. The move is part of Delek’s strategy to expand its operations beyond the Eastern Mediterranean region. Shell, meanwhile, is in the midst of a $10-billion divestment program.
Africa (Sub-Sahara) Cairn Energy has flowed oil from its SNE-2 well offshore Senegal. Drillstem testing of a 39-ft interval achieved a maximum stabilized but constrained flow rate of 8,000 B/D of high-quality pay. A flow rate of 1,000 B/D of relatively low-quality pay was achieved from another zone. Drilled to appraise a 2014 discovery, the well lies in the Sangomar Offshore block in 3,937 ft of water 62 miles from shore. Drilling reached the planned total depth of 9,186 ft below sea level. Cairn has a 40% interest in the block with the other interests held by ConocoPhillips (35%), FAR (15%), and Petrosen (10%).
Africa (Sub-Sahara) Kosmos Energy has made a significant deepwater gas discovery off Senegal. The Guembeul-1 well in the northern part of the St. Louis Offshore Profond license in 8,858 ft of water encountered 331 net ft of gas pay in two excellent-quality reservoirs, the company reported. The results demonstrate reservoir continuity and static pressure communication with the Tortue-1 well, which suggests a single gas accumulation. The mean gross resource estimate for the Greater Tortue complex has risen to 17 Tcf from 14 Tcf as a result of the Guembeul discovery, the company said. Kosmos, the operator, has a 60% interest in the well. Timis (30%) and Petrosen (10%) hold the remaining interest. In Salah Gas has started production from its Southern fields in Algeria.